Kidney Res Clin Pract > Epub ahead of print
Song, Lee, Shin, Kang, Ahn, Baek, Cho, Jung, Lee, Cho, Han, Park, Yang, and Kim: Baseline characteristics and associated factors for hypertension in children with chronic kidney disease: results from the Korean Cohort Study for Outcome in Patients with Pediatric Chronic Kidney Disease study

Abstract

Background

Hypertension is one of the most important complications of chronic kidney disease (CKD) as it exacerbates disease progression in children. The aim of this study is to identify characteristics and factors associated with hypertension in children with CKD.

Methods

This is a cross-sectional study using baseline data from the 10-year ongoing cohort study named KNOW-PedCKD (Korean Cohort Study for Outcome in Patients with Pediatric Chronic Kidney Disease). We enrolled finally 378 patients aged <18 years at seven major pediatric nephrology centers in Republic of Korea. Blood pressure was measured and samples and clinical data were collected during the patients’ annual hospital visits.

Results

We found that 30.7% of the patients had hypertension (n = 116); specifically, 16.4% (n = 62) had systolic hypertension, and 22.8% (n = 86) had diastolic hypertension. Multiple logistic regression analysis indicated that older age (odds ratio [OR], 1.13; p < 0.001), female sex (OR, 2.32; p = 0.002), a high left ventricular mass index (OR, 1.05; p < 0.001), and a high urine protein/creatinine ratio (OR, 1.12; p = 0.02) were significant associated factors for systolic or diastolic hypertension.

Conclusion

This study analyzed the associated factors for hypertension in children with CKD. Hypertension is associated with various factors, including age, sex, heart status, and proteinuria. Therefore, clinicians should consider these factors during patient evaluations to improve health outcomes.

Introduction

The number of individuals with chronic kidney disease (CKD) is gradually increasing, making it a major global public health issue [1]. In children, the prevalence of CKD is approximately 15.0 to 74.7 per million worldwide [2]. Furthermore, the probability of developing CKD in children is also increasing because the outcomes of cancer survivors have continued to improve, prolonging their life expectancy [3].
Due to the increased prevalence of CKD, the global burden of disease studies has reported that CKD is significantly associated with increased worldwide mortality [4]. Several complications, such as hyperkalemia, anemia, rickets, and growth failure caused by pediatric CKD contribute to high mortality and morbidity [5]. Moreover, hypertension is one of the most important damaging comorbidities in children with CKD [6,7]. However, according to data from the United States, early treatment of these complications improved mortality rates in children with CKD over the past 20 years [8]. For example, several cohort studies and trials have highlighted that well-controlled blood pressure (BP) is associated with delayed progression of CKD in children [911].
However, few studies have investigated the rate and associated factors for hypertension as a complication of CKD in children. The Korean Cohort Study for Outcome in Patients with Pediatric Chronic Kidney Disease (KNOW-PedCKD) is a cohort study comprising pediatric patients with CKD conducted for 10 years with funding from the Korean government. This study aims to precisely identify the characteristics and associated factors for hypertension in pediatric patients with CKD.

Methods

Compliance with ethical standards

All enrolled patients provided informed consent from their guardians or the patients themselves according to age. This study was approved by the Institutional Review Boards of the participating centers, namely Pusan National Universi­ty Children’s Hospital (No. 05-2014-025), Severance Hospi­tal (No. 4-2019-1105), Kyungpook National University Hos­pital (No. KNUH-2011-05-002), Seoul National University Hospital (No. 1906-068-1041), Samsung Medical Center (No. 2012-03-063), Asan Medical Center (No. 2011-0436), and Jeju National University Hospital (No. 2014-021-14). It was also registered with the designation NCT02165878 at clinicaltrials.gov (submitted on June 11, 2014).

Study design and population

The KNOW-PedCKD study is a nationwide, prospective, observational cohort study of pediatric patients with CKD in the Republic of Korea funded by the Korean government. Seven major pediatric nephrology centers of the Republic of Korea participated in this 10-year cohort study: Pusan National University Children’s Hospital (Yangsan), Severance Children’s Hospital (Seoul), Kyungpook National University Children’s Hospital (Daegu), Seoul National University Children’s Hospital (Seoul), Samsung Medical Center (Seoul), Asan Medical Center (Seoul), and Jeju University Hospital (Jeju).
The KNOW-PedCKD study commenced in 2011 with the enrollment of 437 patients aged <18 years. As the research progressed, 59 individuals withdrew from participation for reasons such as voluntary withdrawal, leading to a premature exit. By the 7th year, in 2016, a final dataset of 378 individuals was ultimately included in the cross-sectional analysis presented in this paper. Details of the study design and objectives have been previously published [12]. Briefly, for all participating patients, the estimated glomerular filtration rate (eGFR) was calculated following the bedside Chronic Kidney Disease in Children formula [13]. All CKD stages (I to V) were included based on the Kidney Disease Improving Global Outcomes criteria [14]. Patients older than 18 years were excluded from this study because the eGFR formula is different for patients aged >18 years.

Clinical and laboratory collection

Hypertension was defined as an average systolic or diastolic BP value greater than the 95th percentile based on age, sex, and height in individuals under 13 years old [15]. For children aged 13 years and older, it follows the criteria set for adults (hypertension is defined as BP ≥130/80 mmHg) [15]. The BP reference values in this study were based on the 2017 Clinical Practice Guidelines conducted by the American Academy of Pediatrics, the most commonly used guideline worldwide [15]. BP was measured twice manually by auscultation using sphygmomanometers in 5-minute intervals on the right arm after resting in a sitting position. The average of the two measurements was recorded for the systolic and diastolic BPs.
The z scores of weight, height, and body mass index (BMI) were defined according to Korean national growth charts [16]. Weight was classified as follows: within the normal range (–1.65 to 1.65), overweight (≥1.65, corresponding to the highest 5 percentiles), and low weight (<–1.65, corresponding to the lowest 5 percentiles). Height was defined as follows: within the normal range (–1.88 to 1.88), tall stature (≥1.88, corresponding to the highest 5 percentiles), and short stature (<–1.88, corresponding to the lowest 5 percentiles). Similar to weight classification, BMI was also classified as follows: within the normal range (–1.65 to 1.65), high BMI (≥1.65, corresponding to the highest 5 percentiles), and low BMI (<–1.65, corresponding to the lowest 5 percentiles).
We collected data following the KNOW-PedCKD protocol [12], including previously identified laboratory biomarkers that suggest CKD progression or complications (e.g., hemoglobin/ferritin, uric acid, cholesterol, and proteinuria). Additionally, renin and aldosterone levels were measured to determine the presence of activity related to the renin-angiotensin-aldosterone system (RAAS). Family history of hypertension and medication use was also gathered through a self-administered questionnaire during the annual visits. The left ventricular mass (LVM) was measured using two-dimensional and tissue Doppler echocardiography following the Devereux formula [17] as a well-known consequence of hypertension. After then the LVM index (LVMI) was calculated according to the method of de Simone (LVM/height2.7 = g/m2.7) [18].

Statistical analyses

Categorical variables are expressed as percentages, and the chi-square and Fisher exact tests were used for between-group comparisons. The independent t test and Wilcoxon rank-sum test were used for continuous variables, expressed as a means ± standard deviations and median (interquartile range), respectively. Univariable and multivariable logistic regressions were used to estimate the association between characteristics and hypertension. Subsequently, a multiple logistic regression analysis was conducted to identify predictors of heightened BP, adjusting for all confounding factors listed in the table following simple logistic regression. For the odds ratio (OR), OR higher than 1.0 signifies increased values, whereas OR below 1.0 denotes decreased values, and the magnitude reflects the degree of the increase or decrease. The p-value indicating significance was set at <0.05. SAS statistical software (SAS System for Windows, version 9.4; SAS Institute) was used for all statistical analyses.

Results

Participant characteristics and laboratory evaluations

The median age of the total study cohort comprising 378 patients was 11 years old, with 67.2% (n = 254) being male and 32.8% (n = 124) being female. Table 1 presents the characteristics of the included patients with CKD with (n = 62) and without (n = 316) systolic hypertension and with (n = 86) and without (n = 292) diastolic hypertension. Overall, we found that 30.7% of the patients had systolic or diastolic hypertension (n = 116); specifically, 16.4% (n = 62) and 22.8% (n = 86) had systolic and diastolic hypertension, respectively. Female sex (p = 0.004), overweight (p = 0.02), and high BMI (p = 0.001) were identified as significant differences between systolic hypertension and non-systolic hypertension. Older age (p = 0.002) and high BMI (p = 0.02) were significant differences between diastolic hypertension and non-diastolic hypertension.
Table 2 summarizes the laboratory findings and echocardiography for patients with CKD with and without hypertension. The systolic hypertension group had a significantly higher LVMI (p < 0.001) than the non-systolic hypertension group. Additionally, a high uric acid level (p = 0.02), a high ferritin level (p = 0.003), and a low renin level (p = 0.003) were significantly different in CKD patients with diastolic hypertension compared to non-diastolic hypertension.

Associated factors for systolic or diastolic hypertension

First, we performed univariate logistic regression analyses in pediatric patients with CKD and hypertension (Table 3). Independently associated systolic hypertension factors were female sex (OR, 2.21; p = 0.005), low renin level (OR, 0.96; p = 0.02), high LVMI (OR, 1.04; p < 0.001), and shorter disease duration (OR, 0.92; p = 0.02). Independently associated diastolic hypertension factors were older age (OR, 1.11; p < 0.001), high uric acid (OR, 1.18; p = 0.007), high total cholesterol level (OR, 1.00; p = 0.003), low renin level (OR, 0.97; p = 0.02), long gestational age (OR, 1.13; p = 0.03), and high birth weight (OR, 1.61; p = 0.02). Finally, female sex (OR, 1.73; p = 0.02), high ferritin level (OR, 1.00; p = 0.02), low renin level (OR, 0.96; p = 0.003), high LVMI (OR, 1.02; p = 0.005), low serum albumin (OR, 0.62; p = 0.002), low calcium level (OR, 0.74; p = 0.002), and high urine protein/ creatinine ratio (OR, 1.14; p = 0.003) were associated with systolic or diastolic hypertension.
In the multiple logistic regression analysis, high LVMI (OR, 1.04; p < 0.001) was an independent factor associated with systolic hypertension. Furthermore, older age (OR, 1.13, p < 0.001), a high ferritin level (OR, 1.00; p = 0.007), and high total cholesterol (OR, 1.01; p < 0.001) were factors associated with diastolic hypertension. Finally, older age (OR, 1.13; p < 0.001), female sex (OR, 2.32; p = 0.002), and high LVMI (OR, 1.05; p < 0.001) were associated factors of systolic or diastolic hypertension.

Discussion

Hypertension is a well-known hemodynamic risk factor for CKD progression [19] and cardiovascular mortalities [20]. The prevalence of hypertension in pediatric patients with CKD accounts for 50%, as opposed to the 3% to 9% prevalence observed in children without CKD [7,19]. Furthermore, hypertension is more prevalent in children with CKD than in adults [19]. The NAPRTCS (North American Pediatric Renal Transplant Cooperative Study) [6] reported that hypertension is an independent predictor of progression from CKD to end-stage renal disease (ESRD), and the ESCAPE (Effect of Strict Blood Pressure Control and ACE Inhibition on the Progression of Chronic Renal Failure in Pediatric Patients) trial demonstrated that strict BP control slows progression [9]. Therefore, early recognition and strict BP control are crucial for delaying the progression to ESRD in children with CKD. Thus, understanding the associated factors for hypertension is essential to prevent the development and aggravation of hypertension. We designed this study using baseline data from the KNOW-PedCKD cohort, the first Korean prospective cohort study evaluating the associated factors of hypertension in pediatric patients with CKD.
Studies from the United States and Canada reported higher prevalences of hypertension in male than in female [21] and those with a family history of hypertension [22]. The difference in the prevalence of hypertension based on sex among patients with primary hypertension and CKD is attributed to various factors such as hormonal level, vascular structure and function, renal function, genetic factors, and lifestyle factors. In this study, older age was associated factor with diastolic hypertension; however, in the CKiD (Chronic Kidney Disease in Children) study [23], it was observed that children under the age of 7 years had a higher prevalence of elevated BP because of lower prevalence of antihypertensive medication use compared with older children. Therefore, it is necessary to conduct additional studies, such as the use of antihypertension medications based on age, to identify the differences in results regarding the association between age and hypertension in pediatric CKD patients, as observed in this study, compared to other studies. Abnormal lipid metabolism is a well-known risk factor for primary hypertension in children and adolescents [24] similar to those identified in this study. A potential association with diastolic hypertension and abnormal lipid metabolism might occur from impaired endothelial function or an upregulation of the AT1 receptor by low-density lipoprotein cholesterol, potentially leading to an increase in diastolic BP [25]. We found a significantly lower renin level in the systolic and/or diastolic hypertensive groups than in the non-hypertensive group, which was also identified as an associated factor for systolic or diastolic hypertension. This result may be because renin levels varied based on sex, age, BMI, heart function, antihypertensive drug use, and volume status differences [26,27]. Furthermore, some studies have reported an association between elevated uric acid level and hypertension in patients with CKD [28,29], especially in adults with diastolic hypertension [30]. A high uric acid concentration activates RAAS and downregulates nitric oxide production, leading to vasoconstriction and hypertension [31]. Also, unlike some reports that a negative association between BP and gestational age [32], this study suggested that the risk of hypertension is not negatively correlated with gestational age (Table 3). CKD is a complex condition, characterized by various contributing factors. Also, another published systematic review reported that newborns with high birth weight had higher BP during childhood, but lower during adulthood [32]. A long-term follow-up of BP changes in CKD patients is necessary. Therefore, we hypothesized that underlying CKD plays a more significant role than the patients’ birth and family histories. An association between an elevated serum ferritin level and hypertension in the general population has also been reported [33], which can cause oxidative stress, followed by inflammation, endothelial damage, and atherosclerosis, contributing to an elevated BP [34]. This possible mechanism could also apply to patients with CKD. Hypoalbuminemia, caused by systemic inflammatory responses, vascular endothelial injury, and chronic vascular disease, is an important factor contributing to hypertension, and nephrotic range proteinuria is a risk factor for poor BP control, which is why hypoalbuminemia to be associated with hypertension [35,36]. Proteinuria can cause endothelial dysfunction, impaired kidney function, and decreased ability to excrete sodium, elevating the BP [37], and RAAS inhibition plays a vital role in reducing proteinuria and controlling hypertension in pediatric CKD patients. There are a few studies about the relationship between low calcium level and hypertension in CKD patients, and dietary calcium intake has been demonstrated to impact BP in animal studies, which explain that low plasma calcium level stimulates parathyroid hormone and the RAAS, leading to increased vasoconstriction, water reabsorption, and hence BP [38]. Hypertension is also a main contributor to left ventricular hypertrophy (LVH) [7], defined as an LVMI of ≥38 g/m2 and an left ventricular wall thickness z score of >1.64. We also found that LVH might be an associated factor for hypertension in pediatric CKD patients. LVH is a primary target for end-organ damage of hypertension, and increased left ventricular wall stress, such as from hypertension-induced afterload increase, triggers myocardial cell thickening and left ventricular remodeling with activation of RAAS [20]. Therefore, pediatric patients with CKD and a high LVMI should have close BP monitoring. Physicians should also consider antihypertensive treatments to control hypertension and regression if hypertension is confirmed to improve LVMI, cardiovascular outcomes, and mortality risk [20,39].
This study has several limitations. First, this study was a cross-sectional analysis using baseline data from the KNOW-PedCKD, and we could not determine the causal relationship between hypertension and CKD. Thus, a longitudinal follow-up study is needed to determine the causality between hypertension and CKD and confirm the associated factors between hypertension and CKD progression. Second, because ambulatory BP monitoring was not used in this study, the hypertension diagnosis was based on manual BP measurements; thus, measurement errors could have occurred, as well as variability from the BP measurement technique, patient compliance, and the white coat effect. To minimize this potential limitation, we should establish standardized equipment and measurement protocols at all hospitals and train staff in proper BP measurement techniques. Third, this study could not include the patients’ diet and lifestyle parameters, which are also associated with hypertension. Finally, the KNOW-PedCKD includes only ethnically Korean pediatric patients with CKD; therefore, it cannot assess differences between ethnic populations.
In conclusion, various factors are associated with hypertension in pediatric patients with CKD. Our findings suggest that close monitoring of these associated factors could lower the hypertension risk in non-hypertensive patients and prevent CKD progression in hypertensive patients, improving clinical outcomes. Moreover, a longitudinal long-term follow-up study is required to determine the relationship between hypertension and CKD progression.

Notes

Conflicts of interest

All authors have no conflicts of interest to declare.

Funding

This work was supported by the research program funded by the Korea Disease Control and Prevention Agency (2011E3300300, 2012E3301100, 2013E3301600, 2013E3301601, 2013E3301602, 2016E3300200, 2016E3300201, 2016E3300202, 2019E320100, 2019E320101, 2019E320102, 2022-11-007).

Data sharing statement

The data presented in this study are available from the corresponding author upon reasonable request.

Authors’ contributions

Conceptualization: JYS, KHL, JIS, HGK, YHA, MHC, JHL, HC, KHH, SHK

Data curation: YHA, EP

Formal analysis: JYS, YHA, EP

Funding acquisition: HGK

Methodology: KHL, JIS, SHK

Resources: JIS, HGK, MHC, JHL, HC, KHH, SHK

Software: HSB, JJ, EMY

Supervision: JIS, HGK, HSB, MHC, JJ, JHL, HC, KHH, SHK

Visualization: JYS, KHL

Writing–original draft: JYS, KHL

Writing–review & editing: SHK

All authors read and approved the final manuscript.

Acknowledgments

The KNOW-PedCKD study (trial registration: NCT02165878-ClinicalTrials. gov) was supported by the research program funded by the Korea Centers for Disease Control and Prevention (fund codes: 1st year: 2011E3300300, 2nd year: 2012E3301100, 3rd year: 2013E3301600, 4th year: 2013E3301601, 5th year: 2013E3301602, 6th year: 2016E3300200, and 7th year: 2016E3300201). We also greatly acknowledge the help of the following individuals at the Medical Research Collaborating Center (Biomedical Research Institute of Seoul National University Hospital): Heejung Ahn, Sungkyung Kim (data management), and Jayoun Kim and Nanhee Park (biostatistics).

Table 1.
Comparisons of HTN patients and non-HTN patients in CKD cohort study
Characteristic Systolic HTN (n = 62) No HTN (n = 316) p-value Diastolic HTN (n = 86) No HTN (n = 292) p-value
Age (yr) 0.23 0.002
 0–2 8 (12.9) 18 (5.7) 2 (2.3) 24 (8.2)
 2–6 9 (14.5) 54 (17.1) 6 (7.0) 57 (19.5)
 6–12 18 (29.0) 96 (30.4) 26 (30.2) 88 (30.1)
 12–20 27 (43.6) 148 (46.8) 52 (60.5) 123 (42.1)
Sex 0.004 0.21
 Male 32 (51.6) 222 (70.3) 53 (61.6) 201 (68.8)
 Female 30 (48.4) 94 (29.7) 33 (38.4) 91 (31.2)
Etiology 0.81 0.26
 GN 18 (29.0) 87 (27.5) 28 (32.6) 77 (26.4)
 Non-GN 44 (71.0) 229 (72.4) 58 (67.4) 215 (73.6)
CKD stage 0.61 0.44
 I 14 (22.6) 56 (17.7) 14 (16.3) 56 (19.2)
 II 12 (19.4) 89 (28.2) 18 (20.9) 83 (28.4)
 IIIaa 10 (16.1) 54 (17.1) 13 (15.1) 51 (17.5)
 IIIba 13 (21.0) 47 (14.9) 17 (19.8) 43 (14.7)
 IV 11 (17.7) 56 (17.7) 19 (22.1) 48 (16.4)
 V 2 (3.2) 14 (4.4) 5 (5.8) 11 (3.8)
Weight 0.02 0.27
 Low weight 20 (32.3) 80 (25.3) 22 (25.6) 78 (26.7)
 Normal 36 (58.1) 227 (71.8) 58 (67.4) 205 (70.2)
 Overweight 6 (9.7) 9 (2.9) 6 (7.0) 9 (3.1)
Height 0.47 0.90
 Short stature 16 (25.8) 63 (19.9) 19 (22.1) 60 (20.6)
 Normal 46 (74.2) 248 (78.5) 66 (76.8) 228 (78.1)
 Tall stature 0 (0) 5 (1.6) 1 (1.2) 4 (1.4)
Body mass index 0.001 0.02
 Low 4 (6.5) 53 (16.8) 9 (10.5) 48 (16.4)
 Normal 49 (79.0) 250 (79.1) 67 (77.9) 232 (79.5)
 High 9 (14.5) 13 (4.1) 10 (11.6) 12 (4.1)
Family history of HTN 0.99 0.21
 Yes 33 (53.2) 167 (52.9) 51 (59.3) 149 (51.0)
 No 29 (46.8) 146 (46.2) 35 (40.7) 140 (48.0)

Data are expressed as number (%).

CKD, chronic kidney disease; GN, glomerulonephritis; HTN, hypertension.

aCKD stage III is divided into subgroup stages IIIa and IIIb according to the estimated glomerular filtration rate (eGFR; mL/min/1.73 m2); stage IIIa is an eGFR between 45 and 59 and stage IIIb is an eGFR between 30 and 44.

Table 2.
Laboratory and echocardiography differences in pediatric chronic kidney disease patients with and without HTN
Systolic HTN (n = 62) No HTN (n = 316) p-value Diastolic HTN (n = 86) No HTN (n = 292) p-value
Uric acid (mg/dL) 6.10 (2.00–11.00) 6.25 (1.30–14.70) 0.46 6.60 (2.80–12.40) 6.15 (1.30–14.70) 0.02
Hemoglobin (g/dL) 11.75 ± 2.25 12.22 ± 1.87 0.12 11.96 ± 2.23 12.20 ± 1.85 0.37
Ferritin (ng/mL) 50.95 (2.90–2,318.20) 54.05 (4.10–1,272.00) 0.76 65.30 (9.50–2,318.20) 48.80 (2.90–1,272.00) 0.003
Total cholesterol (mg/dL) 170.0 (82.0–481.0) 168.5 (93.0–897.0) 0.93 175.0 (82.0–607.0) 168.0 (93.0–897.0) 0.05
LDL (mg/dL) 94.0 (29.0–321.0) 98.0 (35.0–782.0) 0.85 101.0 (29.0–369.0) 96.0 (35.0–782.0) 0.18
HDL (mg/dL) 48.0 (21.0–97.0) 53.0 (27.0–115.0) 0.38 49.0 (28.0–115.0) 53.0 (21.0–107.0) 0.64
Triglyceride (mg/dL) 131.0 (31.0–1,929.0) 112.5 (30.0–696.0) 0.57 118.0 (47.0–656.0) 112.0 (30.0–1,929.0) 0.27
Renin (ng/mL/hr) 3.7 (0.1–33.5) 6.6 (0.0–80.0) 0.05 3.7 (0.1–80.0) 6.7 (0.0–5.8) 0.003
Aldosterone (pg/mL) 21.7 (0.0–199.0) 22.1 (0.0–634.0) 0.98 20.3 (0.0–199.0) 22.2 (0.0–634.0) 0.36
LVMI (g/m2.7) 43.38 (21.53–243.27) 35.16 (14.89–116.31) <0.001 37.71 (20.95–99.63) 36.26 (14.89–243.27) 0.58

Data are expressed as median (interquartile range) or mean ± standard deviation.

HDL, high-density lipoprotein; HTN, hypertension; LDL, low-density lipoprotein; LVMI, left ventricular mass index.

Table 3.
Associated factors for systolic or diastolic hypertension in patients with chronic kidney disease
Factor Univariable logistic regression
Multivariable logistic regression
Unadjusted OR (95% CI) p-value Adjusted OR (95% CI) p-value
Systolic hypertension
 Age group 0.97 (0.92–1.03) 0.29 - -
 Sex - -
  Male Reference
  Female 2.21 (1.27–3.85) 0.005
 eGFR 1.00 (0.99–1.01) 0.76 - -
 Primary disease 0.81 - -
  Non-glomerulopathy Reference
  Glomerulopathy 1.08 (0.59–1.97)
 BMI z score 1.23 (0.98–1.55) 0.07 - -
 Hemoglobin 0.88 (0.77–1.02) 0.08 - -
 Ferritin 1.00 (0.99–1.00) 0.38 - -
 Uric acid 0.95 (0.83–1.09) 0.44 - -
 Total cholesterol 1.00 (1.00–1.01) 0.31 - -
 LDL 1.00 (1.00–1.01) 0.74 - -
 Renin 0.96 (0.92–0.99) 0.02 - -
 Aldosterone 1.00 (1.00–1.01) 0.83 - -
 LVMI 1.04 (1.02–1.06) <0.001 1.04 (1.02–1.06) <0.001
 Disease duration 0.92 (0.86–0.98) 0.02 - -
 Erythropoietin stimulating use 1.37 (0.55–3.38) 0.498 - -
 Gestational age 1.06 (0.70–1.61) 0.79
 Birth weight 1.13 (0.73–1.74) 0.59
 Family history of hypertension 1.00 (0.58–1.72) 0.99 - -
Diastolic hypertension
 Age group 1.11 (1.05–1.17) <0.001 1.13 (1.06–1.21) <0.001
 Sex - -
  Male Reference
  Female 1.38 (0.83–2.27) 0.21
 eGFR 0.99 (0.99–1.00) 0.08 - -
 Primary disease - -
  Non-glomerulopathy Reference
  Glomerulopathy 1.35 (0.80–2.27) 0.26
 BMI z score 1.07 (0.90–1.28) 0.44 - -
 Hemoglobin 0.94 (0.83–1.06) 0.32 - -
 Ferritin 0.99 (0.93–1.06) 0.71 1.00 (1.00–1.00) 0.007
 Uric acid 1.18 (1.05–1.33) 0.007 - -
 Total cholesterol 1.00 (1.00–1.00) 0.003 1.01 (1.00–1.01) <0.001
 LDL 1.00 (1.00–1.01) 0.02 - -
 Renin 0.97 (0.94–1.00) 0.02 - -
 Aldosterone 0.99 (0.99–1.00) 0.12 - -
 LVMI 1.00 (0.99–1.02) 0.81 - -
 Erythropoietin stimulating use 1.49 (0.73–3.05) 0.27 - -
 Disease duration 1.01 (0.95–1.08) 0.74 - -
 Erythropoietin stimulating use 1.26 (0.58–2.72) 0.56 - -
 Gestational age 1.13 (1.01–1.26) 0.03
 Birth weight 1.61 (1.07–2.40) 0.02
 Family history of hypertension 1.17 (0.68–2.02) 0.58 - -
Systolic or diastolic hypertension
 Age group 1.04 (1.00–1.09) 0.08 1.13 (1.07–1.21) <0.001
 Sex
  Male Reference
  Female 1.73 (1.10–2.73) 0.02 2.32 (1.36–3.95) 0.002
 eGFR 1.00 (0.99–1.00) 0.45
 Primary disease - -
  Non-glomerulopathy Reference
  Glomerulopathy 1.34 (0.83–2.16) 0.24
 BMI z score 1.21 (0.86–1.70) 0.28 - -
 Hemoglobin 0.95 (0.90–1.01) 0.10 - -
 Ferritin 1.00 (1.00–1.00) 0.02 - -
 Total cholesterol 1.00 (1.00–1.01) 0.05 - -
 LDL 1.00 (1.00–1.01) 0.25 - -
 Renin 0.96 (0.94–0.99) 0.003 - -
 Aldosterone 1.00 (0.99–1.00) 0.33 - -
 LVMI 1.02 (1.01–1.04) 0.005 1.05 (1.02–1.07) <0.001
 Serum albumin 0.62 (0.46–0.85) 0.002 - -
 Serum calcium 0.74 (0.61–0.89) 0.002 - -
 Serum phosphorus 1.13 (0.87–1.45) 0.36 - -
 Urine protein/Cr ratio 1.14 (1.05–1.25) 0.003 1.12 (1.02–1.22) 0.02
 Disease duration 0.94 (0.90–1.00) 0.03 - -
 Erythropoietin stimulating use 1.49 (0.73–3.05) 0.27 - -
 Family history of hypertension 1.30 (0.83–2.02) 0.25 - -

BMI, body mass index; CI, confidence interval; Cr, creatinine; eGFR, estimated glomerular filtration rate; LDL, low-density lipoprotein; LVMI, left ventricular mass index; OR, odds ratio.

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ORCID iDs

Ji Yeon Song
https://orcid.org/0000-0002-9665-4177

Keum Hwa Lee
https://orcid.org/0000-0002-1511-9587

Jae Il Shin
https://orcid.org/0000-0003-2326-1820

Hee Gyung Kang
https://orcid.org/0000-0001-8323-5320

Yo Han Ahn
https://orcid.org/0000-0002-8185-4408

Hee Sun Baek
https://orcid.org/0000-0003-0940-360X

Min Hyun Cho
https://orcid.org/0000-0002-7965-7587

Jiwon Jung
https://orcid.org/0000-0001-5358-7966

Joo Hoon Lee
https://orcid.org/0000-0001-8010-3605

Heeyeon Cho
https://orcid.org/0000-0003-3137-6054

Kyoung Hee Han
https://orcid.org/0000-0002-6830-7311

Eujin Park
https://orcid.org/0000-0002-4413-468X

Eun Mi Yang
https://orcid.org/0000-0001-9410-5855

Seong Heon Kim
https://orcid.org/0000-0001-8003-3010

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